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Soft giant magnetoimpedance electronics enable contact-free human-machine interactions.

Yizhang Wu1, Sicheng Xing1, Dingyi Yang2,3

  • 1Department of Applied Physical Sciences, University of North Carolina, Chapel Hill, NC 27599.

Proceedings of the National Academy of Sciences of the United States of America
|January 20, 2026
PubMed
Summary

Researchers developed a new giant magnetoimpedance ionogel (GelGMI) for advanced human-machine interactions. This stretchable, self-healing material offers high sensitivity and neuron-like processing for contact-free control.

Keywords:
flexible electronicsgiant magnetoimpedancehuman–machine interactionsionogelmagnetoelectronics

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Biomedical Engineering

Background:

  • Conventional magnetic films for human-machine interactions (HMI) are limited by rigidity and single-mode sensing.
  • Vacuum deposition methods restrict the flexibility and responsiveness of existing magnetic sensors.

Purpose of the Study:

  • To develop a novel magnetoimpedance ionogel (GelGMI) for advanced, contact-free HMI.
  • To overcome the limitations of conventional rigid magnetic sensors by creating a stretchable and self-healing material.

Main Methods:

  • Electrostatic self-assembly of ferromagnetic (FM) domains within a soft ionogel matrix.
  • Characterization of magnetoimpedance properties under varying magnetic fields and strain.
  • Evaluation of temporal summation and tactile sensing capabilities.

Main Results:

  • GelGMI exhibits pronounced magnetoimpedance with over 1,000% strain tolerance and omnidirectional performance.
  • The material demonstrates neuron-like temporal summation for sequence-aware interactions.
  • A complementary tactile mode enhances recognition capabilities, enabling bimodal sensing.

Conclusions:

  • GelGMI offers a record-high sensitivity for contact-free HMI, unifying stretchability, neuromorphic processing, and self-healing.
  • This material advances the development of next-generation, adaptable human-machine interfaces.
  • The bimodal sensing capability expands the potential applications in robotics and wearable technology.